Latest AI and machine learning research in prevention for healthcare professionals.
The increasing prevalence of chronic diseases related to suboptimal diet quality in the US and worldwide contributes to burgeoning healthcare costs and excess death and disability. Changing dietary intake is essential but difficult because dietary behaviors stem from interconnected biological, psychological, environmental, and social factors that are rarely comprehensively addressed in interventio...
Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2. However, tools for comprehensive, high-resolution analysis of disease-associated changes at the whole-body scale have been lacking. Here we developed MouseMapper, a suite of foundation-model-based deep-learning algorithms enabling multi-system analysis of disease across the entire mo...
OBJECTIVES: To examine the relationship between cardiorespiratory fitness (CRF) and brain aging, and the extent to which this is mediated by systemic ...
BACKGROUND: Cardiac rehabilitation (CR) improves functional capacity and outcomes in patients with heart failure (HF). However, a clinically significa...
Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral ...
OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cance...
The Healthy Eating Index (HEI) is widely used to assess diet quality, but certain contexts (e.g., pregnancy) may benefit from tailored versions. We ev...
BACKGROUND: Artificial intelligence (AI) has significant potential to improve dermatological care, but most studies have concentrated on image-based s...
The objective of this study was to assess ChatGPT's responses to common office ergonomics and spine health questions. ChatGPT was asked the 50 most fr...
Accurate measurement of dry matter intake (DMI) in sheep is logistically challenging and costly, particularly under commercial conditions and across d...
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited myocardial disorder and a major cause of sudden cardiac death in young adul...
BACKGROUND: Early prediction of depressive and anxiety disorders is challenging due to substantial heterogeneity in risk pathways. Conventional machin...
Stroke-related dysphagia is influenced by brain damage location and cognitive impairment, but its mechanisms remain unclear. In this study, we aimed t...
BACKGROUND: The global shortage of psychiatrists limits learners' exposure to authentic patient encounters. Simulation can support scalable deliberate...
BACKGROUND: The gut microbiota adapts to and shapes the host's metabolic state through affecting circulating metabolites and consequent gene regulator...
BACKGROUND: The management of type 2 diabetes requires sustained self-management across diet, physical activity, medication adherence, and blood gluco...
The convergence of Big Data and Artificial Intelligence (AI) is redefining animal nutrition by enabling precision feeding systems that are individuali...
BACKGROUND: Home-based fitness training requires automated systems for exercise quality assessment and real-time posture correction without profession...
Hypertrophic cardiomyopathy (HCM) is the most prevalent genetic cardiac disease and a leading cause of heart failure, arrhythmia, and sudden cardiac d...
With aging, left ventricular (LV) early diastolic lengthening declines. Delayed or dyssynchronous untwisting and relaxation may slow and reduce fillin...